---
title: "Crna Gora COVID-19"
author: "W"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
library(ggplot2)
library(plotly)
library(plyr)
library(flexdashboard)
library(tidyverse)
library(leaflet)
library(stringr)
library(sf)
library(here)
library(widgetframe)
library(tidyr)
library(DT)

mne <- read.csv("/Users/Dovla/Desktop/covidMNE2003.csv")
```

Podaci JIZCG
=======================================================================

Row
-----------------------------------------------------------------------

### Samoizolacija

```{r}
articles <- 6356
valueBox(articles, icon = "fa-home", color = "success")
```

### COVID-19 slucajevi

```{r}
comments <- 53
valueBox(comments, icon = "fa-notes-medical", color = "warning")
```

### Umrli

```{r}
spam <- 1
valueBox(spam, 
         icon = "fa-battery-empty",
         color = "danger")
```


Row
-----------------------------------------------------------------------

### Evolucija COVID-19 slucajeva 

```{r}

mne <- read.csv("/Users/Dovla/Desktop/covidMNE2003.csv")
mne$InfectionRate1 <- as.numeric(levels(mne$InfectionRate))[mne$InfectionRate]
myvars <- c("Day","Infected", "Tested")#, "UnderWatch")
mne1 <- mne[myvars]
#mne1$UnderWatch <- mne1$UnderWatch/10
names(mne1) <- c("Day","covid-19", "Testirano")#, "Izolacija / 10")
mne2 <- mne1 %>%
  pivot_longer(-Day, names_to = "Legenda", values_to = "count")

p11 <- ggplot(mne2, aes(x=Day, y=count,group = Legenda)) + geom_line(aes(linetype=Legenda)) + geom_point() +
    labs(x = "Proslo dana od 09/03/2020 tj prvog dana izvjestavanja o CG", y = "") 
#p11 <- ggplot(mne2, aes(x=Day, y=count, col=series)) + geom_line() + geom_point()
ggplotly(p11)

```

Row
-----------------------------------------------------------------------

### Stopa rasta novih COVID-19 slucajeva

```{r}
p2 <- ggplot(data=mne, aes(x=Day, y=InfectionRate1*100, group=1)) + geom_line(linetype = "dashed", colour="red") +
  geom_point() +
  labs(x = "Proslo dana od 09/03/2020 tj prvog dana izvjestavanja o CG", y = "Stopa u %") 
ggplotly(p2)

```


### Novi COVID-19 slucajevi

```{r}
p3 <- ggplot(data=mne, aes(x=Day, y=InfectedNew)) + geom_bar(stat="identity",color="red", fill="white") +
  labs(x = "Proslo dana od 09/03/2020 tj prvog dana izvjestavanja o CG", y = "Novih slucajeva") 
ggplotly(p3)
```

Spisak i mapa izolovanih
=======================================================================

### Mapa

```{r,echo=FALSE, warning=FALSE}
mapa <- read.csv("/Users/Dovla/Desktop/ime3.csv")
m <- leaflet() %>%
  addTiles(urlTemplate = 'http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png') 
#m %>%
#  frameWidget()
leaflet(data = mapa) %>%
  addTiles() %>%
  addMarkers(clusterOptions = markerClusterOptions())  #%>%  frameWidget()
```

### Spisak

```{r}
mapa1 <- read.csv("/Users/Dovla/Desktop/ime4.csv")
mapa1 %>% 
  dplyr::select(Ime = Ime, Datum = Datum, Grad = Grad, Adresa = Adresa) %>%
  DT::datatable(rownames = FALSE,
            options = list(searchHighlight = TRUE, 
                           pageLength = 20), filter = 'top')
```